




'''simple docstring'''




import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowercase__  							=					get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_sentencepiece
@require_tokenizers
class      UpperCAmelCase_     (  lowerCamelCase__       ,	unittest.TestCase     ):


	"""simple docstring"""


	snake_case									=		ReformerTokenizer
	snake_case									=		ReformerTokenizerFast
	snake_case									=		True
	snake_case									=		False
	snake_case									=		True







	def  _lowercase    (						self				):
						super().setUp()

						snake_case_	=      ReformerTokenizer(__snake_case						, keep_accents=__snake_case				)
						tokenizer.save_pretrained(self.tmpdirname				)







	def  _lowercase    (						self				):
						snake_case_	=      '<s>'
						snake_case_	=      1

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(__snake_case				)						, __snake_case				)
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(__snake_case				)						, __snake_case				)







	def  _lowercase    (						self				):
						snake_case_	=      list(self.get_tokenizer().get_vocab().keys()				)

						self.assertEqual(vocab_keys[0]						, "<unk>"				)
						self.assertEqual(vocab_keys[1]						, "<s>"				)
						self.assertEqual(vocab_keys[-1]						, "j"				)
						self.assertEqual(len(__snake_case				)						, 10_00				)







	def  _lowercase    (						self				):
						self.assertEqual(self.get_tokenizer().vocab_size						, 10_00				)







	def  _lowercase    (						self				):
						if not self.test_rust_tokenizer:
											return

						snake_case_	=      self.get_tokenizer()
						snake_case_	=      self.get_rust_tokenizer()

						snake_case_	=      'I was born in 92000, and this is falsé.'

						snake_case_	=      tokenizer.tokenize(__snake_case				)
						snake_case_	=      rust_tokenizer.tokenize(__snake_case				)
						self.assertListEqual(__snake_case						, __snake_case				)

						snake_case_	=      tokenizer.encode(__snake_case						, add_special_tokens=__snake_case				)
						snake_case_	=      rust_tokenizer.encode(__snake_case						, add_special_tokens=__snake_case				)
						self.assertListEqual(__snake_case						, __snake_case				)

						snake_case_	=      self.get_rust_tokenizer()
						snake_case_	=      tokenizer.encode(__snake_case				)
						snake_case_	=      rust_tokenizer.encode(__snake_case				)
						self.assertListEqual(__snake_case						, __snake_case				)







	def  _lowercase    (						self						, UpperCAmelCase_=15				):
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
											with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''				):
																snake_case_	=      self.rust_tokenizer_class.from_pretrained(__snake_case						, **__snake_case				)

																# Simple input
																snake_case_	=      'This is a simple input'
																snake_case_	=      ['This is a simple input 1', 'This is a simple input 2']
																snake_case_	=      ('This is a simple input', 'This is a pair')
																snake_case_	=      [
																    ('This is a simple input 1', 'This is a simple input 2'),
																    ('This is a simple pair 1', 'This is a simple pair 2'),
																]

																# Simple input tests
																self.assertRaises(__snake_case						, tokenizer_r.encode						, __snake_case						, max_length=__snake_case						, padding="max_length"				)

																# Simple input
																self.assertRaises(__snake_case						, tokenizer_r.encode_plus						, __snake_case						, max_length=__snake_case						, padding="max_length"				)

																# Simple input
																self.assertRaises(
																    __snake_case						, tokenizer_r.batch_encode_plus						, __snake_case						, max_length=__snake_case						, padding="max_length"						, )

																# Pair input
																self.assertRaises(__snake_case						, tokenizer_r.encode						, __snake_case						, max_length=__snake_case						, padding="max_length"				)

																# Pair input
																self.assertRaises(__snake_case						, tokenizer_r.encode_plus						, __snake_case						, max_length=__snake_case						, padding="max_length"				)

																# Pair input
																self.assertRaises(
																    __snake_case						, tokenizer_r.batch_encode_plus						, __snake_case						, max_length=__snake_case						, padding="max_length"						, )







	def  _lowercase    (						self				):
						pass







	def  _lowercase    (						self				):
						snake_case_	=      ReformerTokenizer(__snake_case						, keep_accents=__snake_case				)

						snake_case_	=      tokenizer.tokenize("This is a test"				)
						self.assertListEqual(__snake_case						, ["▁This", "▁is", "▁a", "▁t", "est"]				)

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(__snake_case				)						, [2_85, 46, 10, 1_70, 3_82]						, )

						snake_case_	=      tokenizer.tokenize("I was born in 92000, and this is falsé."				)
						self.assertListEqual(
						    __snake_case						, [
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "9",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "é",
						        ".",
						    ]						, )
						snake_case_	=      tokenizer.convert_tokens_to_ids(__snake_case				)
						self.assertListEqual(
						    __snake_case						, [8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]						, )

						snake_case_	=      tokenizer.convert_ids_to_tokens(__snake_case				)
						self.assertListEqual(
						    __snake_case						, [
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "<unk>",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "<unk>",
						        ".",
						    ]						, )







	@cached_property
	def  _lowercase    (						self				):
						return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment"				)







	@slow
	def  _lowercase    (						self				):
						snake_case_	=      'Hello World!'
						snake_case_	=      [1_26, 32, 2_62, 1_52, 38, 72, 2_87]

						self.assertListEqual(__snake_case						, self.big_tokenizer.encode(__snake_case				)				)







	@slow
	def  _lowercase    (						self				):
						snake_case_	=      (
						    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
						    ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
						)
						snake_case_	=      [
						    1_08,
						    2_65,
						    24,
						    1_11,
						    4,
						    2_58,
						    1_56,
						    35,
						    28,
						    2_75,
						    3,
						    2_59,
						    2_97,
						    2_60,
						    84,
						    4,
						    35,
						    1_10,
						    44,
						    8,
						    2_59,
						    91,
						    2_68,
						    21,
						    11,
						    2_09,
						    2_74,
						    1_09,
						    2_66,
						    2_77,
						    1_17,
						    86,
						    93,
						    3_15,
						    2_58,
						    2_78,
						    2_58,
						    2_77,
						    2_58,
						    0,
						    2_58,
						    2_88,
						    2_58,
						    3_19,
						    2_58,
						    0,
						    2_58,
						    0,
						    2_58,
						    0,
						    2_58,
						    0,
						    2_58,
						    2_87,
						    2_58,
						    3_15,
						    2_58,
						    2_89,
						    2_58,
						    2_78,
						    99,
						    2_69,
						    2_66,
						    2_62,
						    8,
						    2_59,
						    2_41,
						    4,
						    2_17,
						    2_30,
						    2_68,
						    2_66,
						    55,
						    1_68,
						    1_06,
						    75,
						    1_93,
						    2_66,
						    2_23,
						    27,
						    49,
						    26,
						    2_82,
						    25,
						    2_64,
						    2_99,
						    19,
						    26,
						    0,
						    2_58,
						    2_77,
						    1_17,
						    86,
						    93,
						    1_76,
						    1_83,
						    2_70,
						    11,
						    2_62,
						    42,
						    61,
						    2_65,
						]

						self.assertListEqual(__snake_case						, self.big_tokenizer.encode(__snake_case				)				)







	@require_torch
	@slow
	def  _lowercase    (						self				):
						import torch

						from transformers import ReformerConfig, ReformerModel

						# Build sequence
						snake_case_	=      list(self.big_tokenizer.get_vocab().keys()				)[:10]
						snake_case_	=      ' '.join(__snake_case				)
						snake_case_	=      self.big_tokenizer.encode_plus(__snake_case						, return_tensors="pt"				)
						snake_case_	=      self.big_tokenizer.batch_encode_plus([sequence, sequence]						, return_tensors="pt"				)

						snake_case_	=      ReformerConfig()
						# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
						snake_case_	=      encoded_sequence['input_ids'].shape
						snake_case_	=      ReformerModel(__snake_case				)

						# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
						assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

						with torch.no_grad():
											model(**__snake_case				)
											model(**__snake_case				)







	@slow
	def  _lowercase    (						self				):
						# fmt: off
						snake_case_	=      {'input_ids': [[1_08, 2_65, 24, 1_11, 4, 2_58, 1_56, 7, 51, 2_79, 58, 7, 76, 25, 69, 2_78], [1_40, 2_43, 2_64, 1_34, 17, 2_67, 77, 2_63, 22, 2_62, 2_97, 2_58, 3_04, 1_77, 2_79, 2_66, 14, 89, 13, 35, 2_61, 2_99, 2_72, 1_37, 2_75, 2_78]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
						# fmt: on

						# This tokenizer does not know some characters like ")".
						# That is the reason why we use very simple texts here.
						# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
						snake_case_	=      [
						    'This is a very simple sentence.',
						    'The quick brown fox jumps over the lazy dog.',
						]

						self.tokenizer_integration_test_util(
						    expected_encoding=__snake_case						, model_name="google/reformer-crime-and-punishment"						, revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"						, padding=__snake_case						, sequences=__snake_case						, )










'''simple docstring'''






from __future__ import annotations

lowerCAmelCase:   str					=		'Muhammad Umer Farooq'
lowerCAmelCase:   List[str]					=		'MIT'
lowerCAmelCase:   Tuple					=		'1.0.0'
lowerCAmelCase:   List[Any]					=		'Muhammad Umer Farooq'
lowerCAmelCase:   Optional[Any]					=		'contact@muhammadumerfarooq.me'
lowerCAmelCase:   Dict					=		'Alpha'

import re
from html.parser import HTMLParser
from urllib import parse

import requests

class 				a__(   lowerCamelCase__      ):







    def __init__( self					:    Dict		,     __snake_case					:    str      ):
      super().__init__()
      a		:   list[str]	  =	[]
      a		:   List[Any]	  =	domain







    def      lowercase_			( self					:    Dict		,     __snake_case					:    str		,     __snake_case					:    list[tuple[str, str | None]]      ):
      # Only parse the 'anchor' tag.
      if tag == "a":
        # Check the list of defined attributes.
        for name, value in attrs:
          # If href is defined, and not empty nor # print it.
          if name == "href" and value != "#" and value != "":
            # If not already in urls.
            if value not in self.urls:
              a		:   Tuple	  =	parse.urljoin(self.domain		,     __snake_case      )
              self.urls.append(__snake_case      )
def  lowerCamelCase__			(		_A							):
  return ".".join(get_sub_domain_name(_A							).split('.'							)[-2:]							)
def  lowerCamelCase__			(		_A							):
  return parse.urlparse(_A							).netloc
def  lowerCamelCase__			(		_A = "https://github.com"							):
  a		:   Any	  =	get_domain_name(_A							)

  # Initialize the parser
  a		:   Tuple	  =	Parser(_A							)

  try:
    # Open URL
    a		:   List[Any]	  =	requests.get(_A							)

    # pass the raw HTML to the parser to get links
    parser.feed(r.text							)

    # Get links and loop through
    a		:   Union[str, Any]	  =	set()
    for link in parser.urls:
      # open URL.
      # read = requests.get(link)
      try:
        a		:   int	  =	requests.get(_A							)
        # Get the valid email.
        a		:   Optional[Any]	  =	re.findall('[a-zA-Z0-9]+@' + domain					,     read.text							)
        # If not in list then append it.
        for email in emails:
          valid_emails.add(_A							)
      except ValueError:
        pass
  except ValueError:
    raise SystemExit(1							)

  # Finally return a sorted list of email addresses with no duplicates.
  return sorted(_A							)


if __name__ == "__main__":
     lowerCAmelCase:   Any					=		emails_from_url('https://github.com')
     print(F"{len(emails)} emails found:")
     print('\n'.join(sorted(emails)))